Short‐term traffic flow prediction using fuzzy information granulation approach under different time intervals-Reference-Cited by-同舟云学术

Short‐term traffic flow prediction using fuzzy information granulation approach under different time intervals

Published:2017-12-19 Issue:2 Volume:12 Page:143-150
ISSN:1751-9578
Container-title:IET Intelligent Transport Systems
language:en
Short-container-title:IET Intelligent Transport Systems

Author:

Guo Jianhua¹,Liu Zhao¹,Huang Wei¹,Wei Yun²,Cao Jinde³

Affiliation:

1. Intelligent Transportation System Research CenterSoutheast UniversityNanjingPeople's Republic of China

2. Beijing Urban Construction Design and Development Group Co. LtdBeijingPeople's Republic of China

3. School of Mathematics, and Research Center for Complex Systems and Network SciencesSoutheast UniversityNanjingPeople's Republic of China

Funder

National Natural Science Foundation of China

Publisher

Institution of Engineering and Technology (IET)

Subject

Law,Mechanical Engineering,General Environmental Science,Transportation

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1049/iet-its.2017.0144

Reference34 articles.

1. Comparison of parametric and nonparametric models for traffic flow forecasting

2. Integrated Heteroscedasticity Test for Vehicular Traffic Condition Series

3. Data collection time intervals for stochastic short‐term traffic flow forecasting;Guo J.;Transp. Res. Rec.,2008

4. Urban traffic accident time series prediction model based on combination of ARIMA and information granulation SVR;Sun Y.;Tsinghua Sci. Technol.,2014

5. Using interval information granules to improve forecasting in fuzzy time series;Lu W.;Int. J. Approx. Reason.,2015

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